Universiti Teknologi Malaysia Institutional Repository

Automatic pattern recognition of single and multiple power quality disturbances

Khokhar, Suhail and Mohd. Zin, Abdullah Asuhaimi and Mokhtar, Ahmad Safawi and Zareen, Naila (2016) Automatic pattern recognition of single and multiple power quality disturbances. Australian Journal of Electrical and Electronics Engineering, 13 (1). pp. 43-53. ISSN 1448-837X

Full text not available from this repository.

Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

The automatic pattern recognition of single and multiple power quality (PQ) disturbances is a very important task for the detection and monitoring of multiple faults and events in electrical power system. This paper presents an automatic classification algorithm for PQ disturbances based on wavelet norm entropy features and probabilistic neural network (PNN) as an effective pattern classifier. The proposed method employs the discrete wavelet transform based on multi-resolution analysis technique to extract the most important and constructive features of PQ disturbances at various resolution levels. The distinctive norm entropy features of the PQ disturbances have been extracted and were employed as inputs to the PNN. Various other architectures of artificial neural network such as multilayer perceptron and radial basis function neural network have also been employed for comparison. The PNN is found the most suitable pattern recognition tool for the classification of the PQ disturbances. Various PQ disturbances used for analysis were generated by simulating a typical 11-kV distribution system. The simulation results obtained show that the proposed approach can detect and classify the PQ disturbances effectively and can be implemented successfully in real-time electrical power distribution networks.

Item Type:Article
Uncontrolled Keywords:Discrete wavelet transforms, Electric power systems, Entropy, Feature extraction, Multiresolution analysis, Neural networks, Pattern recognition, Pattern recognition systems, Quality control, Radial basis function networks, Two phase flow, Wavelet transforms, Automatic classification, Automatic pattern recognition, Distribution systems, Electrical power system, Norm entropy, Power quality disturbances, Probabilistic neural networks, Radial basis function neural networks, Power quality
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:73981
Deposited By: Fahmi Moksen
Deposited On:23 Nov 2017 06:19
Last Modified:23 Nov 2017 06:19

Repository Staff Only: item control page